Broadcast Data Delivery in IoT Networks with Packet Loss and Energy Constraint

With the rapid development of wireless networks, multiple network interfaces are gradually being designed into more and more mobile devices. When it comes to data delivery, Stream Control Transmission Protocol (SCTP)-based Concurrent Multipath Transfer (CMT) has proven to be quite useful solution for multiple home networks, and it could become the key transport protocol for the next generation of wireless communications. The CMT delay caused by data rearrangement has been noticed by researchers, but they have seldom considered the frequent occurrence of packet loss that occurs in the high-loss networks. In this paper, we proposed an original loss-aware solution for multipath concurrent transmission (CMT-LA) that achieves the following goals: (1) identifying packet loss on all paths, (2) distributing packets adaptively across multiple available paths according to their packet loss and loss variation, and (3) maintaining the features of bandwidth aggregation and parallel transmission of CMT while improving the throughput performance. The results of our simulations showed that the proposed CMT-LA reduces reordering delay and unnecessary fast retransmissions, thereby demonstrating that CMT-LA is a more efficient data delivery scheme than classic CMT.

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Huffman coding packet balancer based data compression techniques in Wireless Sensor Network

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.24.12152 ◽

2018 ◽

Vol 7 (2.24) ◽

pp. 531

Author(s):

Varun Rao ◽

Sandeep Nukala ◽

Abirami G ◽

Deepa R ◽

Revathi Venkataraman

Keyword(s):

Wireless Sensor Network ◽

Sensor Network ◽

Packet Loss ◽

Path Selection ◽

Packet Transmission ◽

Huffman Coding ◽

Wireless Sensor ◽

Data Delivery ◽

Intermediate Node ◽

End To End Delay

In Wireless Sensor Networks, sensor devices perform sensing and communicating task over a network for data delivery from source to destination. Due to the heavy loaded information, during packet transmission, sensor node will drain off its energy frequently, thus led to packet loss. The novelty of the proposed work is mainly reducing the loss of packet and energy consumption during transmission. Thus, Huffman coding packet balancer select the best path between the intermediate nodes and are compared based on transmitting power, receiving and sensing power these measure the QOS in wireless sensor network. To satisfy the QOS of the node, compressed packet from source to destination is done by choosing the best intermediate node path. The advantages of the proposed work is minimum packet loss and minimize the end to end delay. Sparse recovery is used to reconstruct the path selection when there is high density of node.

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Control System Design Considering Packet Loss and Variable Time Delay in a Network-Based System

IEEJ Transactions on Industry Applications ◽

10.1541/ieejias.137.87 ◽

2017 ◽

Vol 137 (2) ◽

pp. 87-94

Author(s):

Tooru Suhara ◽

Hiromu Norizuki ◽

Yutaka Uchimura

Keyword(s):

Control System ◽

Time Delay ◽

System Design ◽

Packet Loss ◽

Control System Design ◽

Variable Time Delay ◽

Variable Time

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A Statistical Testing Method for Accurate Assessment of Packet Loss Probability

IEICE Transactions on Communications ◽

10.1587/transcom.e95.b.2968 ◽

2012 ◽

Vol E95.B (9) ◽

pp. 2968-2971

Author(s):

Iksoon HWANG ◽

Jaesung PARK

Keyword(s):

Packet Loss ◽

Loss Probability ◽

Statistical Testing ◽

Accurate Assessment ◽

Packet Loss Probability ◽

Testing Method ◽

Statistical Testing Method

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Performance Comparison of MANET, VANET and FANET

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v8i5.692 ◽

2018 ◽

Vol 8 (5) ◽

pp. 132

Author(s):

Aarti Sahu ◽

Laxmi Shrivastava

Keyword(s):

Fuzzy Logic ◽

Wireless Network ◽

Packet Loss ◽

Ad Hoc Network ◽

Fuzzy Logic Controller ◽

Ad Hoc ◽

Mobile Ad Hoc Network ◽

Performance Comparison ◽

Fuzzy Rules ◽

Mobile Ad Hoc

A wireless ad hoc network is a decentralized kind of wireless network. It is a kind of temporary Computer-to-Computer connection. It is a spontaneous network which includes mobile ad-hoc network (MANET), vehicular ad-hoc network (VANET) and Flying ad-hoc network (FANET). Mobile Ad Hoc Network (MANET) is a temporary network that can be dynamically formed to exchange information by wireless nodes or routers which may be mobile. A VANET is a sub form of MANET. It is an technology that uses vehicles as nodes in a network to make a mobile network. FANET is an ad-hoc network of flying nodes. They can fly independently or can be operated distantly. In this research paper Fuzzy based control approaches in wireless network detects & avoids congestion by developing the ad-hoc fuzzy rules as well as membership functions.In this concept, two parameters have been used as: a) Channel load b) The size of queue within intermediate nodes. These parameters constitute the input to Fuzzy logic controller. The output of Fuzzy logic control (sending rate) derives from the conjunction with Fuzzy Rules Base. The parameter used input channel load, queue length which are produce the sending rate output in fuzzy logic. This fuzzy value has been used to compare the MANET, FANET and VANET in terms of the parameters Throughput, packet loss ratio, end to end delay. The simulation results reveal that usage of Qual Net 6.1 simulator has reduced packet-loss in MANET with comparing of VANET and FANET.

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A Groundwork Based Novel Routing Protocol for Vehicular Ad hoc Networks

International Journal of Advanced Research in Computer Science and Software Engineering ◽

10.23956/ijarcsse.v7i11.474 ◽

2017 ◽

Vol 7 (11) ◽

pp. 121

Author(s):

Amolkirat Singh ◽

Guneet Saini

Keyword(s):

Routing Protocol ◽

Packet Loss ◽

Secure Communication ◽

Vehicular Ad Hoc Networks ◽

Ad Hoc ◽

Road Traffic ◽

Traditional Approach ◽

Unexpected Events ◽

The Road ◽

On The Road

Many people lose their life and/or are injured due to accidents or unexpected events taking place on road networks. Besides traffic jams, these accidents generate a tremendous waste of time and fuel. Undoubtedly, if the vehicles are provided with timely and dynamic information related to road traffic conditions, any unexpected events or accidents, the safety and efficiency of the transportation system with respect to time, distance, fuel consumption and environmentally destructive emissions can be improved. In the field of computer and information science, Vehicular Ad hoc Network (VANET) have recently emerged as an effective tool for improving road safety through propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. VANET is a research area which is in more demand among the researchers, the automobile industries and scientists to discover about the loopholes and advantages of the vehicular networks so that efficient routing algorithms can be developed which can provide reliable and secure communication among the mobile nodes.In this paper, we propose a Groundwork Based Ad hoc On Demand Distance Vector Routing Protocol (GAODV) focus on how the Road Side Units (RSU’s) utilized in the architecture plays an important role for making the communication reliable. In the interval of finding the suitable path from source to destination the packet loss may occur and the delay also is counted if the required packet does not reach the specified destination on time. So to overcome delay, packet loss and to increase throughput GAODV approach is followed. The performance parameters in the GAODV comes out to be much better than computed in the traditional approach.

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Virtualized Fog Network with Load Balancing for IoT based Fog-to-Cloud

JOIV International Journal on Informatics Visualization ◽

10.30630/joiv.4.3.374 ◽

2020 ◽

Vol 4 (3) ◽

Author(s):

Istabraq M. Al-Joboury ◽

Emad H. Al-Hemiary

Keyword(s):

Load Balancing ◽

Packet Loss ◽

Fog Computing ◽

Transport Protocol ◽

Network Simulator ◽

Huge Number ◽

Message Queue ◽

Limited Bandwidth ◽

Cloud Architecture ◽

Fog Network

Fog Computing is a new concept made by Cisco to provide same functionalities of Cloud Computing but near to Things to enhance performance such as reduce delay and response time. Packet loss may occur on single Fog server over a huge number of messages from Things because of several factors like limited bandwidth and capacity of queues in server. In this paper, Internet of Things based Fog-to-Cloud architecture is proposed to solve the problem of packet loss on Fog server using Load Balancing and virtualization. The architecture consists of 5 layers, namely: Things, gateway, Fog, Cloud, and application. Fog layer is virtualized to specified number of Fog servers using Graphical Network Simulator-3 and VirtualBox on local physical server. Server Load Balancing router is configured to distribute the huge traffic in Weighted Round Robin technique using Message Queue Telemetry Transport protocol. Then, maximum message from Fog layer are selected and sent to Cloud layer and the rest of messages are deleted within 1 hour using our proposed Data-in-Motion technique for storage, processing, and monitoring of messages. Thus, improving the performance of the Fog layer for storage and processing of messages, as well as reducing the packet loss to half and increasing throughput to 4 times than using single Fog server.

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berry tugas jarkom

10.31227/osf.io/5n4sb ◽

2020 ◽

Author(s):

berry clember

Keyword(s):

Packet Loss ◽

Packet Tracer

Koneksi jaringan komputer merupakan suatu hal yang mendasar dalam suatu jaringan karena bila koneksi bermasalah, maka semua jenis aplikasi yang dijalankan melalui jaringan komputer tidak dapat digunakan. Cisco Packet Tracer dapat digunakan untuk simulasi yang mencerminkan gambaran dari koneksi jaringan komputer pada sistem jaringan yang digunakan. Paper ini merancang dua buah perancangan, yakni perancangan dengan topologi mesh dan ring dari empat buah gedung dengan menggunakan software Cisco Packet Tracer dan menghubungkan jaringan antar gedung tersebut dengan perangkat berupa router, serta membandingkan hasil kinerja dari kedua perancangan tersebut. Parameter yang menjadi acuan dalam membandingkan kinerjanya adalah berupa delay, packet loss dan throughput. Dari analisis kinerja jaringan kedua perancangan tersebut untuk Perancangan I dari A ke B, A ke C dan A ke D didapat delay berturut-turut sebesar 114 ms, 110 ms dan 113 ms serta throughput sebesar 0,917 kbps, 1,258 kbps dan 1,638 kbps. Sedangkan untuk perancangan II dari A ke B, A ke C dan A ke D didapat delay berturut-turut sebesar 116 ms, 112 ms dan 140 ms serta throughput sebesar 1,252 kbps, 0,962 kbps dan 0,792 kbps. Sementara packet loss pada kedua perancangan tersebut adalah sama yaitu sebesar 2,5% .

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